System and method for in situ airfoil inspection

Patent metadata

Field	Value
Publication number	US-10914191-B2
Application number	US-201815971236-A
Country	US
Kind code	B2
Filing date	May 4, 2018
Priority date	May 4, 2018
Publication date	Feb 9, 2021
Grant date	Feb 9, 2021

Abstract

An optical in-situ system for a gas turbine engine blade inspection comprises a camera configured to capture images of a forward surface of at least one gas turbine engine blade; and a processor coupled to the camera, the processor configured to determine damage to the at least one gas turbine engine blade based on image analytics.

First claim

What is claimed is:

1. An in-situ system for a gas turbine engine blade inspection comprising:
a sensor system configured to capture images of a forward surface of at least one gas turbine engine blade;
a processor coupled to said sensor system, said processor configured to determine damage to said at least one gas turbine engine blade based on video analytics; and
a tangible, non-transitory memory configured to communicate with said processor, the tangible, non-transitory memory having instructions stored therein that, in response to execution by the processor, cause the processor to perform operations comprising:
receiving, by the processor, data for said forward surface of at least one gas turbine engine blade from said sensor system;
aligning, by the processor, the data with a reference model;
determining, by the processor, a feature dissimilarity between the data and the reference model;
classifying, by the processor, the feature dissimilarity; and
determining, by the processor, a probability that the feature dissimilarity indicates damage to the blade.

2. The in-situ system for gas turbine engine blade inspection of claim 1 , wherein said processor further comprises at least one of a simultaneous localization and mapping process and a structure from motion process program.

3. The in-situ system for gas turbine engine blade inspection of claim 1 , wherein said processor further comprises a model registration process based on blade plane determination.

4. The in-situ system for gas turbine engine blade inspection of claim 1 , wherein said processor further comprises a mosaicking program and a damage detection video analytics program.

5. The in-situ system for gas turbine engine blade inspection of claim 1 , wherein said sensor system is integral with at least one of an engine nacelle and an engine washing system.

6. The in-situ system for gas turbine engine blade inspection of claim 1 , wherein said sensor system comprises lighting comprising at least one of a visible spectrum and an infrared spectrum.

7. The in-situ system for gas turbine engine blade inspection of claim 1 , wherein said sensor system further comprises a shroud configured to protect said sensor from impact damage and debris.

8. The in-situ system for gas turbine engine blade inspection of claim 1 , wherein said gas turbine engine blade is selected from the group consisting of a fan blade, a vane, a compressor blade, a compressor vane, a turbine blade, and a turbine vane.

9. The in-situ system for gas turbine engine blade inspection of claim 1 , wherein said processor is configured to at least one of automatically report damage and archive said damage for at least one of trending and condition-based-maintenance.

10. A method for in-situ inspection of a gas turbine engine blade, comprising:
positioning a sensor to capture images of a forward surface of at least one gas turbine engine blade;
coupling a processor to said sensor, said processor configured to determine damage to said at least one gas turbine engine blade based on image analytics;
wherein said processor performs operations comprising:
receiving, by the processor, data for said forward surface of at least one gas turbine engine blade from said sensor;
aligning, by the processor, the data with a reference model;
determining, by the processor, a feature dissimilarity between the data and the reference model;
classifying, by the processor, the feature dissimilarity; and
determining, by the processor, a probability that the feature dissimilarity indicates damage to the blade.

11. The method for in-situ inspection of a gas turbine engine blade of claim 10 , further comprising: moving said sensor through location and pose variation to image said forward surface of each of said at least one blade of said gas turbine engine.

12. The method for in-situ inspection of a gas turbine engine blade of claim 11 , further comprising:
mosaicking said forward surface of each of said at least one blade of said gas turbine engine into a 3D current condition estimate.

13. The method for in-situ inspection of a gas turbine engine blade of claim 12 , wherein said mosaicking further comprises:
utilizing a simultaneous localization and mapping process.

14. The method for in-situ inspection of a gas turbine engine blade of claim 13 further comprising:
estimating a plane of each of said at least one blade of said gas turbine engine based on said data and said reference model; and
utilizing rotation as a variable.

15. The method for in-situ inspection of a gas turbine engine blade of claim 10 further comprising: archiving said data and said feature dissimilarity for future damage progression detection, damage trending and condition-based maintenance.

16. The method for in-situ inspection of a gas turbine engine blade of claim 10 further comprising: imaging said at least one blade of said gas turbine engine one of continuously and intermittently.

17. The method for in-situ inspection of a gas turbine engine blade of claim 10 wherein said imaging is conducted during gas turbine engine operational conditions selected from the group consisting of coasting, spool-up, and spool-down, including at least one complete revolution.

18. The method for in-situ inspection of a gas turbine engine blade of claim 10 wherein said sensor comprises at least one of, multiple sensors, a video camera, and a depth sensor.

19. The method for in-situ inspection of a gas turbine engine blade of claim 10 wherein said sensor is configured to retract away from exposure to debris.

Assignees

• United Technologies Corp
• Raytheon Tech Corp

Inventors

• Finn Alan Matthew
• Chaudhry Zaffir A

Classifications

• F05D2270/8041

  Cameras · CPC title

• G06T1/0014

  Image feed-back for automatic industrial control, e.g. robot with camera (robots B25J19/023) · CPC title

• G06T2207/10028

  Range image; Depth image; 3D point clouds · CPC title

• F05D2260/80

  Diagnostics · CPC title

• G06T2207/30164

  Workpiece; Machine component · CPC title